# Effect of Construction Land Expansion on Energy-Related Carbon Emissions: Empirical Analysis of China and Its Provinces from 2001 to 2011

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## Abstract

**:**

## 1. Introduction

## 2. Methodology and Data

#### 2.1. Estimation of Energy-Related Carbon Emissions

^{3}for natural gas); $tc{e}_{i}$ denotes the TCE conversion coefficient of energy type i (TCE/t, TCE/m

^{3}for natural gas); and $c{f}_{i}$ denotes the carbon emission coefficient of energy type i (tC/TCE). $C$ denotes the total carbon emissions of the entire country (Mt), which is the sum of carbon emissions of every province. Table 1 shows the parameters for calculating the carbon emissions of major types of fossil energy. Four decimal places were used for calculation accuracy.

Energy | Conversion coefficient of standard coal | Carbon emission coefficient |
---|---|---|

Raw coal | 0.7143 | 0.7559 |

Coke | 0.9714 | 0.8550 |

Crude oil | 1.4286 | 0.5857 |

Gasoline | 1.4714 | 0.5538 |

Kerosene | 1.4714 | 0.5714 |

Diesel | 1.4571 | 0.5921 |

Fuel oil | 1.4286 | 0.6185 |

Natural gas | 13.300 | 0.4483 |

#### 2.2. Decomposition Model of Effect on Carbon Emissions

^{2}). $CO{E}_{ij}$ denotes the carbon emissions coefficient of energy type i in province j; $ST{R}_{ij}$ denotes the proportion of total energy consumption by province j as accounted for by consumption of energy type I; $IN{T}_{j}$ denotes the energy intensity of province j (t/CNY); $IN{C}_{j}$ denotes the per capita economic income of province j (CNY per capita); $DE{N}_{j}$ denotes the population per unit area of construction land in province j (people per km

^{2}); and $EX{P}_{j}$ denotes the area of construction land in province j (km

^{2}). Consequently, carbon emissions could be expressed by the multiplication of carbon emissions coefficient COE, energy consumption structure STR, energy intensity INT, per capita income INC, population density DEN, and construction land expansion EXP. These six factors influence carbon emissions.

_{ij}/E

_{ij}) and structure effect (STR, E

_{ij}/E

_{j}), which can directly reflect the effect of the energy consumption structure. The changing mix of energy (fuel) can make C/E change in time but C

_{ij}/E

_{ij}will be time-invariant. Given that the carbon emission coefficients of each type of energy will remain constant (i.e., the carbon content of each type of energy does not change); thus, we disregarded the effect of COE on carbon emissions. Therefore, $\mathrm{\Delta}{C}_{coe}$ = 0. Thus, the changes in carbon emissions are thus decided by the other five factors as well as the remainder term. On the basis of the articles by Ang, we determined that this method did not produce the remainder term, $\mathrm{\Delta}{C}_{rsd}$ = 0:

#### 2.3. Study Area

#### 2.4. Data Collection and Description

## 3. Results and Discussion

#### 3.1. Analysis of Change Characteristics and Correlation of Carbon Emissions and Construction Land in China

^{2}in 2001 to 43,513.70 km

^{2}in 2011, with an annual growth rate of 6.15%. As shown in Figure 2, carbon emissions and construction land area were increasing from year to year.

**Figure 3.**Change characteristics of provincial carbon emissions and construction land from 2001 to 2011. (

**a**) Emissions and construction land area; (

**b**) Annual growth rate.

#### 3.2. Effect of Construction Land Expansion on Carbon Emissions

**Figure 7.**Distribution of the normalized contribution rates in the two intervals. (

**a**) 2001–2006; (

**b**) 2006–2011.

#### 3.3. Carbon Reduction by Controlling Construction Land Expansion

**Table 2.**Classification of provinces based on the normalized contribution rates of EXP, INC, and INT from 2001 to 2011.

Composite Group No. | Classification Rule | Provinces |
---|---|---|

1 | (high, high, high) | Henan |

2 | (high, high, low) | Shannxi |

3 | (high, low, high) | Shanghai, Jiangxi |

4 | (high, low, low) | Hebei, Shandong, Jiangsu, Zhejiang, Fujian, Guangdong, Yunnan, Chongqing, Ningxia, Xinjiang |

5 | (low, high, high) | Liaoning, Jilin, Heilongjiang, Hubei, Guizhou, Sichuan |

6 | (low, high, low) | Hainan, Inner Mongolia, Hunan, Guangxi, Qinghai |

7 | (low, low, high) | Beijing, Tianjin, Shanxi, Anhui, Gansu |

8 | (low, low, low) | - |

## 4. Conclusions and Policy Implications

## Acknowledgments

## Author Contributions

## Conflicts of Interest

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**MDPI and ACS Style**

Deng, X.; Yu, Y.; Liu, Y.
Effect of Construction Land Expansion on Energy-Related Carbon Emissions: Empirical Analysis of China and Its Provinces from 2001 to 2011. *Energies* **2015**, *8*, 5516-5537.
https://doi.org/10.3390/en8065516

**AMA Style**

Deng X, Yu Y, Liu Y.
Effect of Construction Land Expansion on Energy-Related Carbon Emissions: Empirical Analysis of China and Its Provinces from 2001 to 2011. *Energies*. 2015; 8(6):5516-5537.
https://doi.org/10.3390/en8065516

**Chicago/Turabian Style**

Deng, Xuankai, Yanhua Yu, and Yanfang Liu.
2015. "Effect of Construction Land Expansion on Energy-Related Carbon Emissions: Empirical Analysis of China and Its Provinces from 2001 to 2011" *Energies* 8, no. 6: 5516-5537.
https://doi.org/10.3390/en8065516